[SciPy-User] ANN: Pybroom, a python broom for tidying up messy fit results

[Antonino Ingargiola]

Hi all,

(sorry for cross posting)

===================
Announcing pybroom 0.1
===================

I'm announcing the first public release of pybroom (version 0.1).

Any feedback or suggestions are welcome!

What is pybroom?
==============

Pybroom is a small python 3 library for converting fitting results (curve
fitting or other optimizations) to Pandas DataFrame in tidy format (or
long-form).

DataFrames in tidy format follow a simple rule: one “observation” per row
and one “variable” per column. This simple structure makes it easy to
process the data with clear and well-understood idioms (for filtering,
aggregation, etc.) and allows plot libraries to automatically generate
complex plots in which many variables are compared. Plotting libraries
supporting tidy DataFrames include seaborn, recent versions of matplotlib,
bokeh and altair.

Pybroom was inspired by the R library broom. See this video for details of
the philosophy behind broom:

Example notebooks are included in the pybroom documentation:

http://pybroom.readthedocs.io/en/latest/#example-notebooks

For more details see pybroom homepage:

http://pybroom.readthedocs.io/


Enjoy!

--
Antonino Ingargiola

[Matt Newville]

Hi Antonino,

This looks really nice - I will definitely use this.

Is there anything we should add to lmfit to make these tasks easier? Do
you think there is anything that could be done to make ModelResult or
similar "result" of a fit be made more "tidy" in this sense? Would it make
sense to add a "tidy()" method to a ModelResult that did some of this work?


--Matt